多功能雷达脉冲列的语义编码与模型重建

刘章孟; 袁硕; 康仕乾

doi:10.12000/JR21031

多功能雷达脉冲列的语义编码与模型重建

DOI: 10.12000/JR21031

国防科技大学电子科学学院长沙 410073

基金项目: 湖南省杰青(2020JJ2037)，湖湘青年英才支持计划(2019RS2026)，湖南省创新研究群体项目(2019JJ10004)

详细信息

作者简介:
刘章孟(1984–)，男，湖北天门人，国防科技大学电子科学学院研究员。研究方向为电子侦察与对抗、电磁大数据、统计信号处理

袁　硕(1997–)，男，山东济南人，国防科技大学电子科学学院硕士研究生。研究方向为雷达侦察数据处理

康仕乾(1996–)，男，河北衡水人，国防科技大学电子科学学院硕士研究生。研究方向为雷达侦察数据处理

通讯作者:
刘章孟 liuzhangmeng@nudt.edu.cn

责任主编：唐斌 Corresponding Editor: TANG Bin
中图分类号: TN971
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出版历程
- 收稿日期: 2021-03-15
- 修回日期: 2021-07-23
- 网络出版日期: 2021-08-28

Semantic Coding and Model Reconstruction of Multifunction Radar Pulse Train

School of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China

Funds: Provincial Outstanding Youth project of Hunan (2020JJ2037), Huxiang Young Talents project of Hunan (2019RS2026), Provincial Innovation Research Group of Hunan (2019JJ10004)

More Information

Corresponding author: LIU Zhangmeng, liuzhangmeng@nudt.edu.cn

摘要

摘要: 从电子侦察数据中反演多功能雷达的工作模式，是电子侦察领域广泛关注的难点问题，也是充分挖掘电磁大数据情报效益的重要内容，对雷达型号识别、工作状态识别、行为意图推断、精确电子干扰等应用具有直接的支撑作用。该文以多功能雷达信号模型的简洁性为基本依据，参考信息理论定义了雷达脉冲列的复杂度度量规则，并遵循复杂度最小化准则对多功能雷达脉冲列进行语义编码，以提取雷达执行不同功能时的脉组结构，进一步地，基于脉冲列编码序列估计脉组之间的切换矩阵，从而重建了多功能雷达工作模型。该文设置典型的仿真实验对新方法的可行性和性能进行了验证，结果表明新方法能够借助编码理论，自动从多功能雷达侦察脉冲列中准确提取雷达脉组，并高精度重建多功能雷达工作模型，脉冲列的语义编码与模型重建过程对漏脉冲等数据噪声具有较强的适应能力。
- 电子侦察 /
- 多功能雷达 /
- 数据压缩 /
- 语义编码 /
- 模型重建
Abstract: Retrieving the working modes of multifunction radar from electronic reconnaissance data is a difficult problem, and it has attracted widespread attention in the field of electronic reconnaissance. It is also an important task when extracting benefits from big electromagnetic data and provides straightforward support to applications, such as radar type recognition, working state recognition, radar intention inferring, and precise electronic jamming. Based on the assumption of model simplicity, this study defines a complexity measurement rule for multifunction radar pulse trains and introduces the semantic coding theory to analyze the temporal structure of multifunction radar pulse trains. The model complexity minimization criterion guides the semantic coding procedure to extract radar pulse groups corresponding to different radar functions from pulse trains. Furthermore, based on the coded sequence of the pulse train, the switching matrix between different pulse groups is estimated, and the hierarchical working model of multifunction radars is ultimately reconstructed. Simulations are conducted to verify the feasibility and performance of the new method. Simulation results indicate that the coding theory is successfully used in the proposed method to automatically extract pulse groups and rebuild operating models based on multifunction radar pulse trains. Moreover, the method is robust to data noises, such as missing pulses.
- Electronic reconnaissance /
- Multifunctional radars /
- Data compression /
- Semantic coding /
- Model reconstruction

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图 1 多功能雷达的工作模式示意图

Figure 1. Schematic diagram of the working mode of multifunctional radar

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图 2 多功能雷达的脉组结构

Figure 2. Pulse group structure of multifunctional radar

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图 3 多功能雷达脉冲列的层次化时序结构

Figure 3. Hierarchical temporal structure of multifunctional radar pulse train

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图 4 雷达脉冲列的层次化结构中蕴含了语义信息

Figure 4. Semantic information is contained in the hierarchical structure of multifunctional radar pulse train

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图 5 多功能雷达侦察脉冲列示意图

Figure 5. Schematic diagram of reconnaissance pulse train of multifunctional radar

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图 6 多功能雷达脉冲列编码模型寻优流程

Figure 6. Optimization process of the coding model of multifunctional radar pulse train

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图 7 多功能雷达脉组状态转移矩阵估计精度随脉组数目的变化情况

Figure 7. Estimation accuracy of the state transition matrix of multifunction radar pulse group with respect to different number of pulse groups

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图 8 多功能雷达脉组重建正确率随漏脉组率的变化情况

Figure 8. Probability of correct pulse group reconstruction with respect to different missing ratios of pulse groups

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表 1 脉冲列迭代编码过程中顺次输出的脉组字典集

Table 1. Sequentially extracted pulse group dictionary set from pulse train during iterative coding process

迭代次数	脉组字典集
迭代次数	脉组 (µs)	频次
1	229.98	98
2	229.98, 330.00	98
3	229.98, 330.00, 430.00	98
4	229.98, 330.00, 430.00 284.98	98 109
5	229.98, 330.00, 430.00 355.97, 284.98	98 109
6	229.98, 330.00, 430.00 407.00, 355.97, 284.98	98 109
7	229.98, 330.00, 430.00 407.00, 355.97, 284.98 299.98	98 109 93
8	229.98, 330.00, 430.00 407.00, 355.97, 284.98 299.98, 304.99	98 109 93
9	229.98, 330.00, 430.00 407.00, 355.97, 284.98 299.98, 304.99, 310.01	98 109 93

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表 2 脉组切换次数统计结果

Table 2. Switching number between different pulse groups

	脉组1	脉组2	脉组3
脉组1	28	36	33
脉组2	44	18	31
脉组3	26	39	44

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表 3 漏脉组率为50%条件下的脉组提取结果

Table 3. Extracted pulse groups from a pulse train with 50% pulse missing

脉组序号	脉组(µs)	频次
1	[230.02, 329.98, 429.98]	65
2	[230.02, 329.98]	52
3	[300.00, 304.93, 309.98]	46
4	[300.00, 304.93]	37
5	[407.03, 355.97, 284.97]	41
6	[407.03, 355.97]	59

下载: 导出CSV

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